scholarly journals Chronic Low-Dose Exposure to Xenoestrogen Ambient Air Pollutants and Breast Cancer Risk: XENAIR Protocol for a Case-Control Study Nested Within the French E3N Cohort (Preprint)

2019 ◽  
Author(s):  
Amina Amadou ◽  
Thomas Coudon ◽  
Delphine Praud ◽  
Pietro Salizzoni ◽  
Karen Leffondre ◽  
...  

BACKGROUND Breast cancer is the most frequent cancer in women in industrialized countries. Lifestyle and environmental factors, particularly endocrine-disrupting pollutants, have been suggested to play a role in breast cancer risk. Current epidemiological studies, although not fully consistent, suggest a positive association of breast cancer risk with exposure to several International Agency for Research on Cancer Group 1 air-pollutant carcinogens, such as particulate matter, polychlorinated biphenyls (PCB), dioxins, Benzo[a]pyrene (BaP), and cadmium. However, epidemiological studies remain scarce and inconsistent. It has been proposed that the menopausal status could modify the relationship between pollutants and breast cancer and that the association varies with hormone receptor status. OBJECTIVE The XENAIR project will investigate the association of breast cancer risk (overall and by hormone receptor status) with chronic exposure to selected air pollutants, including particulate matter, nitrogen dioxide (NO2), ozone (O3), BaP, dioxins, PCB-153, and cadmium. METHODS Our research is based on a case-control study nested within the French national E3N cohort of 5222 invasive breast cancer cases identified during follow-up from 1990 to 2011, and 5222 matched controls. A questionnaire was sent to all participants to collect their lifetime residential addresses and information on indoor pollution. We will assess these exposures using complementary models of land-use regression, atmospheric dispersion, and regional chemistry-transport (CHIMERE) models, via a Geographic Information System. Associations with breast cancer risk will be modeled using conditional logistic regression models. We will also study the impact of exposure on DNA methylation and interactions with genetic polymorphisms. Appropriate statistical methods, including Bayesian modeling, principal component analysis, and cluster analysis, will be used to assess the impact of multipollutant exposure. The fraction of breast cancer cases attributable to air pollution will be estimated. RESULTS The XENAIR project will contribute to current knowledge on the health effects of air pollution and identify and understand environmental modifiable risk factors related to breast cancer risk. CONCLUSIONS The results will provide relevant evidence to governments and policy-makers to improve effective public health prevention strategies on air pollution. The XENAIR dataset can be used in future efforts to study the effects of exposure to air pollution associated with other chronic conditions. INTERNATIONAL REGISTERED REPORT DERR1-10.2196/15167

10.2196/15167 ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. e15167 ◽  
Author(s):  
Amina Amadou ◽  
Thomas Coudon ◽  
Delphine Praud ◽  
Pietro Salizzoni ◽  
Karen Leffondre ◽  
...  

Background Breast cancer is the most frequent cancer in women in industrialized countries. Lifestyle and environmental factors, particularly endocrine-disrupting pollutants, have been suggested to play a role in breast cancer risk. Current epidemiological studies, although not fully consistent, suggest a positive association of breast cancer risk with exposure to several International Agency for Research on Cancer Group 1 air-pollutant carcinogens, such as particulate matter, polychlorinated biphenyls (PCB), dioxins, Benzo[a]pyrene (BaP), and cadmium. However, epidemiological studies remain scarce and inconsistent. It has been proposed that the menopausal status could modify the relationship between pollutants and breast cancer and that the association varies with hormone receptor status. Objective The XENAIR project will investigate the association of breast cancer risk (overall and by hormone receptor status) with chronic exposure to selected air pollutants, including particulate matter, nitrogen dioxide (NO2), ozone (O3), BaP, dioxins, PCB-153, and cadmium. Methods Our research is based on a case-control study nested within the French national E3N cohort of 5222 invasive breast cancer cases identified during follow-up from 1990 to 2011, and 5222 matched controls. A questionnaire was sent to all participants to collect their lifetime residential addresses and information on indoor pollution. We will assess these exposures using complementary models of land-use regression, atmospheric dispersion, and regional chemistry-transport (CHIMERE) models, via a Geographic Information System. Associations with breast cancer risk will be modeled using conditional logistic regression models. We will also study the impact of exposure on DNA methylation and interactions with genetic polymorphisms. Appropriate statistical methods, including Bayesian modeling, principal component analysis, and cluster analysis, will be used to assess the impact of multipollutant exposure. The fraction of breast cancer cases attributable to air pollution will be estimated. Results The XENAIR project will contribute to current knowledge on the health effects of air pollution and identify and understand environmental modifiable risk factors related to breast cancer risk. Conclusions The results will provide relevant evidence to governments and policy-makers to improve effective public health prevention strategies on air pollution. The XENAIR dataset can be used in future efforts to study the effects of exposure to air pollution associated with other chronic conditions. International Registered Report Identifier (IRRID) DERR1-10.2196/15167


2019 ◽  
Vol 19 (5) ◽  
pp. e563-e577 ◽  
Author(s):  
Elham Vahednia ◽  
Fatemeh Homaei Shandiz ◽  
Matineh Barati Bagherabad ◽  
Atefeh Moezzi ◽  
Fahimeh Afzaljavan ◽  
...  

2018 ◽  
Vol 244 (1) ◽  
pp. 63-73 ◽  
Author(s):  
Yoko Takizawa ◽  
Masaaki Kawai ◽  
Yoichiro Kakugawa ◽  
Yoshikazu Nishino ◽  
Noriaki Ohuchi ◽  
...  

2014 ◽  
Vol 136 (10) ◽  
pp. 2378-2387 ◽  
Author(s):  
Valentina Assi ◽  
Nathalie J. Massat ◽  
Susan Thomas ◽  
James MacKay ◽  
Jane Warwick ◽  
...  

2019 ◽  
Vol 3 ◽  
pp. 231-232
Author(s):  
Lemarchand C ◽  
Gabet S ◽  
Tvardik N ◽  
Cénée S ◽  
Slama R ◽  
...  

2016 ◽  
Vol 54 (2) ◽  
pp. 111-113 ◽  
Author(s):  
D Gareth Evans ◽  
Adam Brentnall ◽  
Helen Byers ◽  
Elaine Harkness ◽  
Paula Stavrinos ◽  
...  

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mariem Hajji-Louati ◽  
Emilie Cordina-Duverger ◽  
Nasser Laouali ◽  
Francesca-Romana Mancini ◽  
Pascal Guénel

AbstractDietary regimens promoting inflammatory conditions have been implicated in breast cancer development, but studies on the association between pro-inflammatory diet and breast cancer risk have reported inconsistent results. We investigated the association between the inflammatory potential of diet and breast cancer risk in a case–control study in France including 872 breast cancer cases and 966 population controls. All women completed a food frequency questionnaire that was used to compute a Dietary Inflammatory Index (DII) based on the inflammatory weight of 33 dietary components. The DII ranged from a median of − 3.22 in the lowest quartile (anti-inflammatory) to + 2.96 in the highest quartile (pro-inflammatory). The odds ratio contrasting quartile 4 to quartile 1 was 1.31 (95% CI 1.00, 1.73; p-trend = 0.02). Slightly higher odds ratios were observed in post-menopausal women, particularly those with body mass index > 25 kg/m2 (odds ratio 1.62; 95% CI 0.92, 2.83; p-trend = 0.02), and among ever smokers (odds ratio 1.71; 95% CI 1.11, 2.65; p-trend 0.01). The analyses by breast cancer subtype showed that the DII was associated with breast tumors that expressed either the estrogen (ER) or progesterone (PR) hormone receptors or the Human Epidermal Growth Factor Receptor-2 (HER2), but no association was seen for the triple negative breast tumor subtype. Our results add further evidence that a pro-inflammatory diet is associated with breast cancer risk with possible effect variation according to tumor subtype.


2011 ◽  
Vol 48 (10) ◽  
pp. 698-702 ◽  
Author(s):  
R. L. Milne ◽  
J. Lorenzo-Bermejo ◽  
B. Burwinkel ◽  
N. Malats ◽  
J. I. Arias ◽  
...  

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